A method for evaluating the efficacy grade of tea hydrolat based on antioxidant activity spectrum

Abstract

The application discloses a kind of tea hydrolat efficacy grade evaluation methods based on antioxidant activity spectrum, comprising: collecting tea hydrolat sample;Multi-index antioxidant activity spectrum is constructed, at least three kinds of indexes in DPPH clearance capacity, ABTS clearance capacity, FRAP reduction capacity, metal ion chelation capacity and lipid peroxidation inhibition capacity are determined;Quantitative analysis at least two kinds of tea characteristic components in total phenol, tea polyphenol, theaflavin, linalool and geraniol;Z-score standardization is carried out to measured value;Index weight is determined using entropy weight method, and antioxidant comprehensive index AOCI is calculated;Principal component analysis is carried out;Based on AOCI value and comprehensive score, tea hydrolat is divided into four efficacy grades of special grade, first grade, second grade and third grade using K-means clustering method;Fisher discriminant model is established to realize fast grade prediction.The application constructs tea hydrolat "antioxidant activity spectrum" evaluation system, overcomes one-sidedness of single index evaluation, and provides scientific basis for quality control, process optimization and high-value utilization of tea hydrolat product.

Description

Technical Field

[0001] This invention relates to the field of tea deep processing and quality evaluation technology, specifically to a method for evaluating the antioxidant efficacy of tea hydrosol products in the tea processing industry chain. By constructing a multi-index antioxidant activity spectrum and combining it with chemometric analysis, the method enables scientific grading and quality identification of the antioxidant efficacy of different varieties and processed tea hydrosols. Background Technology

[0002] Tea hydrosol is an important product of the intensive processing of tea. It is a natural plant hydrate extracted from tea leaves through steam distillation. Tea hydrosol is rich in volatile aroma components and water-soluble active substances from tea, such as linalool in white tea, geraniol and theaflavins in black tea, and tea polyphenols in raw tea. These components endow tea hydrosol with excellent antioxidant, anti-inflammatory, and soothing effects. With the rapid development of the tea processing industry, the application of tea hydrosol in cosmetics, functional foods, and aromatherapy is becoming increasingly widespread.

[0003] However, in the tea processing industry, the following technical deficiencies still exist in the quality evaluation of new deep-processed tea products such as tea hydrosol: One drawback is the reliance on a single evaluation indicator, which fails to comprehensively reflect the antioxidant quality of tea hydrosols. Antioxidant efficacy is a core quality indicator of tea hydrosols. Current technologies often use a single antioxidant indicator (such as DPPH free radical scavenging rate) for evaluation, commonly using a DPPH scavenging rate ≥90% as a quality control indicator. However, tea contains a wide variety of antioxidant components with complex mechanisms of action, involving free radical scavenging, metal ion chelation, reducing power, and lipid peroxidation inhibition. A single indicator only reflects one aspect of antioxidant capacity and cannot comprehensively evaluate the overall antioxidant quality of tea hydrosols. Furthermore, the antioxidant material basis differs among different tea varieties—white tea is primarily composed of linalool, black tea of ​​theaflavins and geraniol, and raw Pu-erh tea of ​​tea polyphenols—making it difficult to distinguish their quality differences using a single indicator.

[0004] The second deficiency is the lack of a systematic efficacy evaluation standard suitable for the tea processing industry: Currently, the quality control of tea hydrosols mainly focuses on conventional physicochemical indicators (pH value, relative density) and microbiological indicators, without a systematic evaluation method or grading standard for antioxidant efficacy. In the tea processing industry, the antioxidant efficacy of tea hydrosols prepared under different varieties, origins, and processing conditions varies significantly, but existing standards cannot scientifically evaluate and grade these differences. This results in high-quality tea hydrosol products being unable to be effectively distinguished from ordinary products, hindering the intensive processing and high-value utilization of tea resources.

[0005] The third deficiency is that the correlation between antioxidant activity and characteristic components of tea remains unclear: Although studies have reported that tea hydrosols possess antioxidant activity, a quantitative correlation model between antioxidant activity and characteristic active components of tea has not been established. The contributions of characteristic components of tea, such as linalool in white tea, theaflavins in black tea, and tea polyphenols in raw tea, to antioxidant activity differ, but current technology has failed to elucidate this correlation. This makes it impossible to explain the source and differences in antioxidant efficacy from the perspective of tea raw material characteristics, which is detrimental to guiding the optimization of tea processing techniques.

[0006] Fourthly, there is a lack of quantitative evaluation indicators for optimizing tea processing techniques: Due to the lack of scientific efficacy evaluation methods, the optimization of tea hydrosol production processes (such as the selection of distillation temperature, time, and material-to-liquid ratio) mainly relies on traditional indicators such as sensory evaluation and yield, and there is a lack of quantitative evaluation basis for improving antioxidant efficacy. At the same time, it is difficult to effectively monitor the consistency of product quality between batches from an efficacy perspective, which restricts the standardized production of tea hydrosol products.

[0007] In conclusion, developing a method applicable to the tea processing industry that can comprehensively and scientifically evaluate the antioxidant effects of tea hydrosols and classify them is of significant theoretical and practical value for improving the level of deep processing technology for tea and promoting the high-value utilization of tea resources. Summary of the Invention

[0008] The purpose of this invention is to overcome the technical deficiencies in the existing tea processing industry, such as the single evaluation index of tea hydrosol efficacy, the lack of systematic grading standards, and the unclear correlation between antioxidant activity and tea components. This invention provides a method suitable for tea hydrosol products, which constructs a comprehensive antioxidant index based on a multi-index antioxidant activity spectrum and establishes an efficacy grading evaluation model by combining tea characteristic component analysis and chemometric methods.

[0009] To achieve the above objectives, the present invention adopts the following technical solution: a method for evaluating the efficacy grade of tea hydrosol based on antioxidant activity spectrum, comprising the following steps: S1. Collection and preparation of tea hydrosol samples Tea hydrosol samples were collected from different varieties, origins, batches, and processing conditions, including white tea hydrosol, black tea hydrosol, and raw Pu-erh tea hydrosol. Three replicates were prepared for each sample, which were stored at 4℃ for later use. Samples must be clear and transparent, free of sediment and suspended matter.

[0010] The method for preparing the tea hydrosol is as follows: take tea raw materials, add purified water at a material-to-liquid ratio of 1:20, steam distill for 30 minutes at the corresponding temperature (95℃ for white tea, 90℃ for black tea, and 90℃ for raw tea), collect the distillate, filter it through a 0.22μm membrane for sterilization, and then fill it with nitrogen.

[0011] S2. Construction of a multi-index antioxidant activity spectrum The following five antioxidant indicators were measured for each sample, with each indicator measured three times and the average value taken. All measurements must be completed within 24 hours to ensure sample freshness.

[0012] S2.1 Determination of DPPH free radical scavenging ability Reagent preparation: Accurately weigh 3.94 mg of DPPH, dissolve it in anhydrous ethanol and dilute to 100 mL to obtain a 0.1 mmol / L DPPH solution, and store it protected from light.

[0013] Determination Procedure: Take 0.1 mL of tea hydrosol sample, add 3.9 mL of DPPH solution, vortex to mix, and react at room temperature in the dark for 30 minutes. Zero the sample with anhydrous ethanol and measure the absorbance (sample A) at 517 nm. Simultaneously measure the absorbance (blank) of 0.1 mL anhydrous ethanol + 3.9 mL DPPH solution, and the absorbance (control) of 0.1 mL sample + 3.9 mL anhydrous ethanol.

[0014] Results calculation: DPPH free radical scavenging rate (%) = [1 - (Sample A - Control A) / Blank A] × 100% Precision requirement: RSD of parallel samples < 5%.

[0015] S2.2 Determination of ABTS free radical scavenging ability Reagent preparation: Mix an equal volume of 7 mmol / L ABTS solution with 2.45 mmol / L potassium persulfate solution and react at room temperature in the dark for 12-16 hours to prepare ABTS stock solution. Before use, dilute with PBS (pH 7.4) to an absorbance of 0.70 ± 0.02 at 734 nm to obtain ABTS working solution.

[0016] Measurement procedure: Add 0.1 mL of sample to 3.9 mL of ABTS working solution, vortex to mix, and react at room temperature in the dark for 6 minutes. Measure the absorbance of sample A at 734 nm. Simultaneously measure the absorbance of blank A (0.1 mL PBS + 3.9 mL ABTS working solution).

[0017] Results calculation: ABTS clearance rate (%) = (A blank - A sample) / A blank × 100%.

[0018] Standard curve: Prepare a series of Trolox standard solutions (0, 0.1, 0.2, 0.4, 0.6, 0.8, 1.0 mmol / L), determine the concentrations according to the above method, plot the standard curve, and calculate the total antioxidant capacity of the sample, expressed in μmol Trolox / mL.

[0019] S2.3 FRAP Reducing Capacity Determination (1) Reagent preparation: 300 mmol / L acetate buffer (pH 3.6): Weigh 3.1 g sodium acetate, add 16 mL glacial acetic acid, and dilute to 1 L with water.

[0020] 10 mmol / L TPTZ solution: Weigh 31.2 mg TPTZ, dissolve it in 40 mmol / L hydrochloric acid and bring the volume to 10 mL.

[0021] 20 mmol / L FeCl3 solution: Weigh 54.1 mg FeCl3·6H2O, dissolve in water and dilute to 10 mL.

[0022] FRAP working solution: Mix acetate buffer, TPTZ solution and FeCl3 solution in a ratio of 10:1:1, and prepare fresh before use.

[0023] Measurement procedure: Take 0.1 mL of sample, add 3.0 mL of FRAP working solution, vortex to mix, react in a 37℃ water bath for 10 minutes, and measure the absorbance of sample A at 593 nm.

[0024] Standard curve: Prepare a series of FeSO4 standard solutions (0, 100, 200, 400, 600, 800, 1000 μmol / L), determine the concentrations according to the above method, plot the standard curve, and calculate the reducing power of the sample, expressed in μmol FeSO4 / L.

[0025] S2.4 Determination of metal ion chelation ability (1) Reagent preparation: 2 mmol / L FeCl2 solution: Weigh 39.8 mg FeCl2·4H2O, dissolve in water and dilute to 100 mL.

[0026] 5 mmol / L phenanthroxazine solution: Weigh 49.3 mg of phenanthroxazine, dissolve in water and dilute to 25 mL.

[0027] Determination procedure: Take 1.0 mL of sample, add 3.7 mL of methanol, 0.1 mL of FeCl2 solution, and 0.2 mL of phenanthroxazine solution, vortex to mix, react at room temperature for 10 minutes, and measure the absorbance of sample A at 562 nm. At the same time, measure the absorbance of blank A using 1.0 mL of water instead of sample A.

[0028] Results calculation: Metal ion chelation rate (%) = (A blank - A sample) / A blank × 100%.

[0029] S2.5 Determination of lipid peroxidation inhibition capacity (ferric thiocyanate method) Liposome preparation: Weigh 300 mg of lecithin, dissolve it in 30 mL of PBS (pH 7.4), sonicate it in an ice bath for 30 minutes to prepare a liposome suspension, and store it at 4°C for later use.

[0030] Measurement steps: Take 1.0 mL of liposome suspension, add 0.5 mL of sample, 0.2 mL of FeCl3 solution (400 μmol / L), and 0.2 mL of ascorbic acid solution (400 μmol / L), and make up to 4.0 mL with PBS, then mix well.

[0031] React at 37°C in the dark for 1 hour, then add 0.2 mL of TCA solution (20%) and 0.2 mL of TBA solution (1%), heat in a boiling water bath for 15 minutes, and then cool.

[0032] Add 2.0 mL of n-butanol for extraction, and measure the absorbance of the n-butanol layer at 500 nm for sample A.

[0033] Simultaneously, the absorbance of the control tube (A control) without any sample was measured.

[0034] (3) Calculation of results: Lipid peroxidation inhibition rate (%) = (A control - A sample) / A control × 100% S3. Quantitative analysis of characteristic active ingredients in tea S3.1 Determination of total phenol content (Folin-Ciocalteu method) Reagent preparation: Folin-Ciocalteu reagent was diluted 10 times with distilled water; the Na2CO3 solution concentration was 7.5%.

[0035] Standard curve: Prepare a series of gallic acid standard solutions of various concentrations (0, 10, 20, 40, 60, 80, 100 mg / L).

[0036] Measurement procedure: Take 0.5 mL of sample, add 2.5 mL of diluted Folin-Ciocalteu reagent, react for 5 minutes, add 2.0 mL of Na2CO3 solution, mix well, react at room temperature in the dark for 60 minutes, and measure the absorbance at 765 nm.

[0037] Results calculation: The total phenol content of the sample was calculated based on the standard curve and expressed as mg gallic acid equivalent (GAE) / L.

[0038] S3.2 Determination of tea polyphenol content (ferrous tartrate colorimetric method) (1) Reagent preparation: Ferrous tartrate solution: Weigh 1.0g FeSO4·7H2O and 5.0g potassium sodium tartrate, dissolve in water and dilute to 1L.

[0039] pH 7.5 phosphate buffer: Weigh 60.2g Na2HPO4·12H2O and 5.0g NaH2PO4·2H2O, dissolve in water and bring the volume to 1L.

[0040] (2) Measurement procedure: Take 1.0 mL of sample, add 4.0 mL of water and 5.0 mL of ferrous tartrate solution, and make up to 25 mL with pH 7.5 phosphate buffer. Mix well and measure the absorbance at 540 nm.

[0041] Results calculation: Tea polyphenol content (mg / L) = absorbance × 3.913 × dilution factor.

[0042] S3.3 Determination of theaflavin content (ethyl acetate extraction-colorimetric method) Measurement steps: Take 30 mL of sample and extract twice with 30 mL of ethyl acetate, then combine the organic phases.

[0043] The organic phase was washed twice with 15 mL of 2.5% NaHCO3 solution each time, and the aqueous phase was discarded.

[0044] The organic phase was evaporated to dryness, and the residue was dissolved in methanol and brought to a final volume of 10 mL.

[0045] The absorbance was measured at 380 nm.

[0046] (2) Calculation of results: A standard curve was established using theaflavin standard, and the theaflavin content (mg / L) of the sample was calculated.

[0047] S3.4 Determination of characteristic aroma components of tea (GC-MS method) Sample pretreatment: Take 10 mL of sample, add 2 mL of dichloromethane, vortex for 2 minutes, sonicate for 10 minutes, centrifuge at 4000 rpm for 10 minutes, take the lower organic phase, filter through a 0.22 μm organic phase membrane, and prepare for analysis.

[0048] GC-MS conditions: Column: DB-Heavy Wax (30m × 250μm × 0.5μm) Inlet temperature: 250℃ Programmed temperature rise: Initial temperature 50℃, hold for 2 min, increase to 240℃ at 5℃ / min, hold for 5 min. Carrier gas: High-purity helium, flow rate 1.0 mL / min Injection volume: 1 μL, split ratio 10:1 Ion source temperature: 250℃ Transmission line temperature: 250℃ Electron bombardment source: 70 eV Scan range: m / z 35-550 Acquisition rate: 10 spectra / s.

[0049] (3) Qualitative and quantitative analysis: Qualitative analysis was performed by searching the NIST spectral library, and the relative contents of characteristic aroma components of tea such as linalool and geraniol were calculated by peak area normalization method.

[0050] S4. Standardization of Antioxidant Activity Profile The Z-score method was used to standardize the values ​​of the five antioxidant indicators measured in S2. The calculation formula is as follows: Zij = (Xij - Xj) / Sj Where: Zij is the standardized value of the j-th index of the i-th sample; Xij is the original measured value of the j-th index of the i-th sample; Xj is the average value of the j-th index of all samples; and Sj is the standard deviation of the j-th index of all samples.

[0051] S5. Calculation of the Overall Antioxidant Index (AOCI) The entropy weight method was used to objectively determine the weights of each indicator and calculate the comprehensive antioxidant index.

[0052] S5.1 Determining Weights Using the Entropy Weight Method Calculate the proportion of the i-th sample under the j-th indicator: Pij = Zij / Σ(i=1 to n) Zij, where n is the total number of samples; Calculate the entropy value of the j-th index: ej = -k × Σ(i=1 to n)(Pij×ln Pij), where k = 1 / ln(n); Calculate the difference coefficient of the j-th indicator: gj = 1 - ej; Calculate the weight of the j-th indicator: Wj=gj / Σ(j=1 to m)gj, where m is the total number of indicators; S5.2 Calculate the comprehensive antioxidant index AOCIi =Σ(j=1 to m) (Wj×Zij) S6. Principal Component Analysis Principal component analysis was performed on the standardized antioxidant index data: Calculate the correlation coefficient matrix R; Find the eigenvalues ​​λk and eigenvectors of R; Principal components were extracted based on the principle that eigenvalues ​​> 1. Calculate the scores of each principal component: PCik = Σ(j=1 to m)(Ljk×Zij); Calculate the overall principal component score: PC_overall score = Σ(k=1 to p)(λk / Σλk × PCik).

[0053] S7. Cluster Analysis and Hierarchical Classification Based on AOCI values ​​and comprehensive principal component scores, K-means clustering was used to classify tea hydrosol samples into four efficacy levels: premium, first-grade, second-grade, and third-grade.

[0054] S8. Establishment of Fisher's Discriminant Model Fisher's discriminant function was established using DPPH scavenging rate, ABTS value, total phenolic content, and theaflavins content as discriminant variables to rapidly predict the efficacy level of unknown tea hydrosol samples. Leave-one-out cross-validation was used to evaluate the model's accuracy, requiring ≥85%.

[0055] S9. Methodological Validation This includes precision testing, repeatability testing, stability testing, and spike recovery testing, and all indicators must meet the requirements.

[0056] Compared with the prior art, the present invention has the following beneficial effects. 1. For the first time, an evaluation system for the "antioxidant activity spectrum" of tea hydrosols applicable to the tea processing industry was constructed. This invention expands a single antioxidant index into a multi-index activity spectrum encompassing five different antioxidant mechanisms: DPPH free radical scavenging, ABTS free radical scavenging, FRAP reducing capacity, metal ion chelating capacity, and lipid peroxidation inhibition capacity. This comprehensively reflects the overall antioxidant quality of tea hydrosols. Experiments have shown that different types of tea hydrosols exhibit varying performance across these indicators: white tea hydrosol has the highest DPPH scavenging rate (91.5%), black tea hydrosol has the highest lipid peroxidation inhibition rate (72.5%), and raw tea hydrosol has the best FRAP value (168.5 μmol / L) and metal chelating rate (51.2%). A single index cannot reflect these multi-dimensional differences, while the activity spectrum of this invention can comprehensively characterize the antioxidant properties of various types of tea hydrosols.

[0057] 2. Establish an Antioxidant Comprehensive Index (AOCI) based on the entropy weight method. This invention employs the entropy weight method to objectively determine the weight coefficients of each antioxidant index, eliminating the arbitrariness of subjective weighting. The lipid peroxidation inhibition rate, due to its greatest difference among samples, receives the highest weight (0.252), while the metal chelation rate, due to its smallest difference, receives the lowest weight (0.155). This weight allocation reflects the characteristics of the data itself and conforms to statistical principles. Based on this, the constructed AOCI value can scientifically quantify the comprehensive antioxidant capacity of tea hydrosol samples, achieving a leap from qualitative to quantitative analysis.

[0058] 3. To reveal the quantitative correlation between the antioxidant activity of tea hydrosols and the characteristic components of tea. Correlation analysis revealed a significant positive correlation between the antioxidant activity of white tea hydrosol and linalool content (r=0.82), the antioxidant activity of black tea hydrosol and theaflavins content (r=0.88), and the antioxidant activity of raw tea hydrosol and total phenolic content (r=0.91). This finding reveals that the material basis for the antioxidant effects of different types of tea hydrosols originates from the tea leaves themselves, providing a scientific basis for raw material selection and process optimization in tea processing.

[0059] 4. Pioneering a standard for classifying the efficacy grades of tea hydrosols. Based on AOCI values ​​and cluster analysis results, tea hydrosols were classified into four efficacy grades for the first time: Premium (AOCI ≥ 0.8), Grade 1 (0 ≤ AOCI < 0.8), Grade 2 (-0.8 ≤ AOCI < 0), and Grade 3 (AOCI < -0.8). Statistical analysis of the grade distribution of 45 samples showed that Premium products accounted for 13.3%-26.7%, Grade 1 products for 40.0%-53.4%, Grade 2 products for 26.6%-26.7%, and Grade 3 products for 6.6%-6.7%. The grade distribution was reasonable and the differentiation was good, providing a scientific quality grading standard for the tea processing industry.

[0060] 5. Establish a rapid grading prediction model based on Fisher's criteria. Fisher's discriminant function was established using four key indicators: DPPH scavenging rate, ABTS value, total phenolic content, and theaflavins content. The accuracy of predicting the grade of unknown tea hydrosol samples reached 91.7% (with leave-one-out cross-validation), with a validation set accuracy of 100%. This model only requires measuring four indicators to quickly determine the sample grade, significantly improving evaluation efficiency and making it suitable for online quality control in tea processing production lines.

[0061] 6. Support the optimization of tea processing techniques and standardized production. This method can provide a quantitative evaluation basis for optimizing the production process of tea hydrosols. By comparing the AOCI values ​​of samples at different distillation temperatures, the optimal process parameters can be determined (e.g., the optimal distillation temperature for black tea hydrosol is 90℃). Simultaneously, by monitoring the fluctuations in AOCI values ​​between batches, quality control to ensure consistent product efficacy can be achieved, thereby improving the standardization level of processed tea products.

[0062] 7. The methodology is thoroughly validated and highly reliable. The precision test RSD < 5%, the repeatability test RSD < 8%, the stability test RSD < 10%, and the spiked recovery rate 95%-105% all met the requirements, indicating that the method has good accuracy, reliability and operability, and is suitable for promotion and application in the tea processing industry. Attached Figure Description

[0063] Figure 1 Radar charts of antioxidant activity spectra of different types of tea hydrosols are shown. The charts demonstrate the differences in the performance of white tea hydrosol, black tea hydrosol, and raw Pu-erh tea hydrosol in five antioxidant indicators, intuitively reflecting the antioxidant characteristics of each type of tea hydrosol.

[0064] Figure 2 Principal component analysis scores for the antioxidant properties of tea hydrosols are shown in the figure. The figure illustrates the distribution of 45 tea hydrosol samples in the principal component space, with distinct clusters formed between different tea types, indicating that this method has good discriminative ability.

[0065] Figure 3 This diagram illustrates the distribution and grading of AOCI values ​​for tea hydrosols. The diagram shows the AOCI value distribution for each tea hydrosol sample and indicates the grading thresholds for four grades: premium, first-grade, second-grade, and third-grade. Detailed Implementation

[0066] The following is in conjunction with the appendix Figures 1-3 The specific implementation of the method for evaluating the efficacy level of tea hydrosol based on the antioxidant activity spectrum of the present invention will be further described in detail.

[0067] Example 1: Construction and grading of antioxidant activity spectra of different tea hydrosol varieties 1. Sample Source Samples W1-W15: White tea hydrosol (15 batches, prepared by steam distillation at 95℃ for 30 minutes using Fuding Da Bai tea as raw material, with a material-to-liquid ratio of 1:20).

[0068] Samples R1-R15: Black tea hydrosol (15 batches, prepared by steam distillation at 90℃ for 30 minutes using Meizhan black tea as raw material, with a material-to-liquid ratio of 1:20).

[0069] Samples G1-G15: Pu-erh raw tea hydrosol (15 batches, prepared by steam distillation at 90℃ for 30 minutes using Yunnan large-leaf sun-dried green tea as raw material, with a material-to-liquid ratio of 1:20).

[0070] Antioxidant activity spectrum determination results The measurement results are shown in Table 1 below. Figure 1 The radar chart shows that different types of tea hydrosols exhibit significant differences in five antioxidant indicators: white tea hydrosol has the highest DPPH scavenging rate (91.5%), black tea hydrosol has the highest lipid peroxidation inhibition rate (72.5%), while raw Pu-erh tea hydrosol leads in FRAP reducing capacity (168.5 μmol / L) and metal chelation rate (51.2%).

[0071] Table 1:

[0072] The results of the determination of the content of characteristic components in tea are shown in Table 2.

[0073] Table 2:

[0074] Entropy weight method for calculating weights Based on standardized data from 45 samples, the weights of each indicator were calculated using the entropy weight method, and the results are shown in Table 3. The lipid peroxidation inhibition rate received the highest weight (0.252) due to the greatest difference among samples, while the metal chelation rate received the lowest weight (0.155) due to the smallest difference.

[0075] Table 3:

[0076] AOCI value calculation and classification The AOCI values ​​for each sample were calculated, and the results are shown in Table 4. Figure 3 As shown, the AOCI values ​​of the 45 samples range from -0.92 to +1.42. Based on the cluster analysis results, they can be divided into four levels: Special Level (AOCI ≥ 0.8), Level 1 (0 ≤ AOCI < 0.8), Level 2 (-0.8 ≤ AOCI < 0), and Level 3 (AOCI < -0.8).

[0077] Table 4:

[0078] Correlation analysis of characteristic components of tea and antioxidant activity The results of the correlation analysis are shown in Table 5. Figure 2 As can be seen from the principal component analysis score plot, the samples of the three tea categories form clearly separated clusters in the principal component space, indicating that this method has a good ability to distinguish varieties.

[0079] Table 5:

[0080] The results showed that the antioxidant activity of different types of tea hydrosols was significantly positively correlated with their respective characteristic tea components, revealing that the material basis for the antioxidant effects of tea hydrosols comes from the tea itself.

[0081] Example 2: Comparison of the antioxidant activity spectra of black tea hydrosols produced by different distillation processes Sample preparation Using the same batch of Meizhan black tea as raw material, black tea hydrosol samples were prepared by steam distillation at 0℃, 90℃ and 100℃ for 30 minutes at a material-to-liquid ratio of 1:20. Three parallel samples were prepared at each temperature.

[0082] Measurement results The measurement results are shown in Table 6. Figure 2As shown in the principal component analysis score plot, samples prepared at different temperatures are distributed in different positions in the principal component space, with the sample prepared at 90℃ being closer to the region with high antioxidant activity.

[0083] Table 6:

[0084] Results Analysis The black tea hydrosol prepared under distillation conditions at 90℃ exhibited the best antioxidant properties across all indicators, with an AOCI value of 1.18, classifying it as a premium product. Samples prepared at 0℃ and 100℃ showed lower antioxidant activity, classified as Grade II and Grade I, respectively. These results demonstrate that this evaluation method can provide a quantitative basis for optimizing tea processing techniques, identifying 90℃ as the optimal extraction temperature for black tea hydrosol, consistent with the temperature requirements for aroma component retention during tea processing.

[0085] Example 3: Establishment and Validation of Fisher's Discriminant Model Training set samples Thirty-six samples were selected from the 45 samples in Example 1 as the training set, including samples of each level: 8 premium samples, 12 first-level samples, 10 second-level samples, and 6 third-level samples.

[0086] Discriminant variable selection Through stepwise discriminant analysis, DPPH scavenging rate (X1), ABTS value (X2), total phenol content (X3), and theaflavin content (X4) were selected as discriminant variables.

[0087] Fisher discriminant function Establish three Fisher discriminant functions: Y1=0.285X1+3.124X2+0.032X3+0.215X4-12.56 Y2=0.176X1+2.185X2+0.018X3+0.142X4-8.32 Y3 =0.092X1+1.536X2+0.009X3+0.087X4-5.18 Judgment rules Calculate the scores of the sample on the three discriminant functions, and take the group corresponding to the maximum score as the predicted level of the sample.

[0088] Verification results Using the remaining 9 samples as the validation set, the back-validation was performed with 100% accuracy. Leave-one-out cross-validation had an accuracy of 91.7%.

[0089] Example 4: Methodological Validation Results All validation indicators met the requirements: precision RSD < 5%, repeatability RSD < 8%, stability RSD < 10%, and spike recovery rate 95%-105%.

[0090] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. Any improvements and modifications made by those skilled in the art without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A method for evaluating the efficacy grade of tea hydrosols based on antioxidant activity spectrum, characterized in that, Includes the following steps: (1) Collection and preparation of tea hydrosol samples: Collect tea hydrosol samples prepared under different varieties, origins, batches and process conditions; (2) Construction of multi-index antioxidant activity spectrum: At least three different antioxidant mechanisms were measured for each sample to obtain antioxidant activity spectrum data; (3) Quantitative analysis of characteristic active ingredients in tea: quantitative detection of characteristic active ingredients in tea samples; (4) Standardization of antioxidant activity spectrum: The measured values ​​of various antioxidant indicators were standardized by Z-score; (5) Calculation of the Antioxidant Comprehensive Index (AOCI): Based on the standardized antioxidant index values, the entropy weight method is used to determine the weight of each index and calculate the Antioxidant Comprehensive Index (AOCI). (6) Principal component analysis: Principal component analysis was performed on the standardized antioxidant index data to extract principal components and calculate the comprehensive score; (7) Cluster analysis and classification: Based on the AOCI value and the comprehensive principal component score, the K-means clustering method was used to classify the tea hydrosol samples into different efficacy levels; (8) Establishment of Fisher discriminant model: Fisher discriminant function is established based on key indicators for rapid prediction of efficacy level of unknown tea hydrosol samples.

2. The evaluation method according to claim 1, characterized in that, The antioxidant indicators mentioned in step (2) include at least three of the following: DPPH free radical scavenging ability, ABTS free radical scavenging ability, FRAP reducing ability, metal ion chelating ability, and lipid peroxidation inhibition ability.

3. The evaluation method according to claim 1, characterized in that, The characteristic active ingredients of tea mentioned in step (3) include at least two of the following: total phenols, tea polyphenols, theaflavins, linalool and geraniol.

4. The evaluation method according to claim 1, characterized in that, The steps for determining the weights using the entropy weight method described in step (5) include: calculating the proportion of the standardized values ​​of each sample under each indicator, calculating the entropy value of each indicator, calculating the difference coefficient of each indicator, and calculating the weight of each indicator based on the difference coefficient.

5. The evaluation method according to claim 1, characterized in that, The efficacy levels described in step (7) are divided into four levels: special grade, first grade, second grade and third grade. The classification criteria are determined based on the distribution characteristics of AOCI values ​​and the results of cluster analysis.

6. The evaluation method according to claim 5, characterized in that, The AOCI value range corresponding to the special grade is AOCI ≥ 0.8, the AOCI value range corresponding to the first grade is 0 ≤ AOCI < 0.8, the AOCI value range corresponding to the second grade is -0.8 ≤ AOCI < 0, and the AOCI value range corresponding to the third grade is AOCI < -0.

8.

7. The evaluation method according to claim 1, characterized in that, The key indicators mentioned in step (8) include at least three of the following: DPPH scavenging rate, ABTS value, total phenol content, and theaflavin content.

8. The evaluation method according to claim 1, characterized in that, The Fisher discrimination model described in step (8) is validated using leave-one-out cross-validation, and the discrimination accuracy is ≥85%.

9. The evaluation method according to claim 1, characterized in that, The tea hydrosol is selected from at least one of white tea hydrosol, black tea hydrosol, or raw Pu-erh tea hydrosol.

10. The evaluation method according to claim 1, characterized in that, It also includes a methodology validation step, which includes at least one of precision testing, repeatability testing, stability testing, and spiked recovery testing.

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